Browsing by Author "Wei, Cheng-Wen"

Now showing 1 - 7 of 7

Analysis and implementation of low-power perceptual multiband noise reduction for the hearing aids application
(2014-11-01)
Wei, Cheng-Wen
;
Tsai, Cheng-Chun
;
Yi FanJiang
;
Chang, Tian-Sheuan
;
Jou, Shyh-Jye
Traditional noise reduction designs provide good performance but suffer from high complexity and long latency, which limits their application to hearing aids. Targeted for strict low-power and low-latency requirement of completely-in-the-canal type hearing aids, this study analyses and implements a previously proposed sample-based perceptual multiband spectral subtraction with a multiplication-based entropy voice activity detection. Simulation results reveal that the authors design can provide similar speech quality as others, but with lower computational complexity and simple control effort. The corresponding core-based architecture design further exploits processing characteristics of the proposed approach to reduce power consumption with a sign-magnitude and a preprocessed input data reuse scheme. Chip measurement shows that the design only consumes 83.7 mu W at 0.6 V operation with 90 nm high threshold voltage (HVT) (high V-T) standard cell library.
Low Complexity Formant Estimation Adaptive Feedback Cancellation for Hearing Aids Using Pitch Based Processing
(2014-08-01)
Yi FanChiang
;
Wei, Cheng-Wen
;
Meng, Yi-Le
;
Lin, Yu-Wen
;
Jou, Shyh-Jye
This paper proposes a novel algorithm and architecture for the adaptive feedback cancellation (AFC) based on the pitch and the formant information for hearing aid (HA) applications. The proposed method, named as Pitch based Formant Estimation (PFE-AFC), has significantly low complexity compared to Prediction Error Method AFC (PEM-AFC). The proposed PFE-AFC consists of a forward and a backward path processing. The forward path processing includes a low complexity pitch based formant estimator for decorrelation filter coefficients update and a pitch based voice activity detector for speech detection, which facilitates the feedback cancellation filter in the backward path to reduce feedback component and maintain speech quality. From system point of view, the PFE-AFC has low complexity overhead since it is easy to share computation resource with other components in the HA system, such as noise reduction and auditory compensation. In addition, the PFE-AFC is suitable for hardware implementation owing to its regular structure. Complexity evaluations show that the PFE-AFC has four orders lower complexity than the PEM-AFC. Simulation results show that the PFE-AFC and the PEM-AFC can achieve similar PESQ (perceptual evaluation speech quality) and ASG (added stable gain). Moreover, the proposed PFE-AFC can outperform the conventional AFC.
Low Computational Complexity Pitch Based VAD for Dynamic Environment in Hearing Aids
(2010-01-01)
Chen, Yu-Jui
;
Wei, Cheng-Wen
;
Meng, Yi-Le
;
Jou, Shyh-Jye
;
電機學院
This paper presents a low computational complexity and high robust voice activity detection (VAD) algorithm. The algorithm is based on an efficient time-domain pitch detection and harmonic structure discrimination exploiting frequency decomposition by 1/3 octave filter bank defined in ANSI S1.11 standard. In addition, a simple yet efficient phoneme keeper (PK) is adopted for the detection of monosyllable languages, such as Mandarin. Simulation results reveal that the proposed VAD has very robust performance for Mandarin speeches in different environments, even for dynamic SNR (signal to noise ratio) and noise type. Furthermore, in white noise with 0dB SNR, the proposed VAD still has about 90 percent accuracy.
Low Computational Complexity Pitch Based VAD for Dynamic Environment in Hearing Aids
(2011)
Chen, Yu-Jui
;
Wei, Cheng-Wen
;
Meng, Yi-Le
;
Jou, Shyh-Jye
;
電子工程學系及電子研究所
This paper presents a low computational complexity and high robust voice activity detection (VAD) algorithm. The algorithm is based on an efficient time-domain pitch detection and harmonic structure discrimination exploiting frequency decomposition by 1/3 octave filter bank defined in ANSI S1.11 standard. In addition, a simple yet efficient phoneme keeper (PK) is adopted for the detection of monosyllable languages, such as Mandarin. Simulation results reveal that the proposed VAD has very robust performance for Mandarin speeches in different environments, even for dynamic SNR (signal to noise ratio) and noise type. Furthermore, in white noise with 0dB SNR, the proposed VAD still has about 90 percent accuracy.
Neuromorphic Pitch Based Noise Reduction for Monosyllable Hearing Aid System Application
(2014-02-01)
Chen, Yu-Jui
;
Wei, Cheng-Wen
;
Yi FanChiang
;
Meng, Yi-Le
;
Huang, Yi-Cheng
This paper presents a low computational complexity hardware-oriented neuromorphic pitch based noise reduction (NR) algorithm and hardware implementation for monosyllable hearing aid system applications. The proposed NR design consists of a pitch-based voice activity detector (pitch-based VAD) for speech detection and a neuromorphic noise attenuator for speech enhancement. The pitch-based VAD is developed on ANSI S1.11 based filter bank architecture and employs the characteristics of monosyllable and nonlinear energy operator (NEO) to improve the accuracy of VAD. The neuromorphic noise attenuator reduces the background noise by using the characteristics of human hearing system and the clues of speech. Simulation results show that the proposed algorithm has better SNR and PESQ performance than other non-pitch based NR algorithms in non-stationary background noise environments. Compared with multiband (mband) spectral subtraction and minimum mean square error (mmse) algorithms, the computational complexity of the proposed algorithm can save 90% computational complexity. The hardware implementation consumes 47.74 mu W at 0.5 V operation with 65 nm HVT standard cell library.
Perceptual Multiband Spectral Subtraction for Noise Reduction in Hearing Aids
(2010)
Wei, Cheng-Wen
;
Tsai, Cheng-Chun
;
Chang, Tian-Sheuan
;
Jou, Shyh-Jye
;
電子工程學系及電子研究所
This paper presents a low complexity noise reduction method by a perceptual multiband spectral subtraction for CIC type hearing aids. The noisy speech is first perceptually decomposed by a 1/3 octave filter bank by ANSI S1.11, and the noise is estimated by an enhanced entropy based voice activity detection (VAD), and then noise is subtracted by a simple multiband spectral subtraction. Simulations show that under different environments the proposed algorithm averagely improves segmental SNR (Signal to Noise Ratio) and PESQ (Perceptual Evaluation of Speech Quality) by 6.27dB and 0.32, respectively, and performs better compared to the previous approach. In addition, informal listening test shows there is not musical noise in the processed speech.
Sub mu W Noise Reduction for CIC Hearing Aids
(2012-05-01)
Wei, Cheng-Wen
;
Su, Sheng-Jie
;
Chang, Tian-Sheuan
;
Jou, Shyh-Jye
;
電子工程學系及電子研究所
This paper presents a sub W noise reduction design to enhance speech for completely-in-the-canal (CIC) type hearing aids by optimizing its algorithm and associated architecture. In algorithm optimization, a low-complexity mixed perceptual-discrete wavelet packet transform (P-DWPT) and fast Hartley transform (FHT) are adopted for spectral decomposition and reconstruction. A simple yet efficient denoise method with 4-zone-voice activity detection (VAD) supports a consonant protection to improve speech quality and a skip scheme to reduce power consumption. In the designed architecture, mixed P-DWPT and FHT are folded into one 8-by-8 configurable butterfly computation unit with on-time scheduling for low power operation. The circuit is implemented with 0.18-mu m CMOS process and consumes only 0.65 mu W power at 1.0 V with a speech quality that is comparable to that achieved using other high-complexity algorithms.